Applications of Federated Learning in Technological Advancements: Use Cases and Applications [Hardcover]

1. Journey Towards Federated Learning: Fundamentals, Tools Paradigms, Opportunities and Challenges 2. Federated Learning-based algorithms for deployment and model optimization 3.???? Automation of AI and IoT-based Data-driven Decision-Making Approaches using Federated Learning Systems 4. Federated Learning for sustainable development using IoT/Edge Computing Systems 5.? Advances in 5G/6G enabled federated reinforcement learning in IoT 6. Blockchain Integrated Federated Learning for IoT-based Smart?Applications 7. Federated Learning in Heterogeneous Unmanned Aerial Vehicle 8. Advanced Technologies for Federated learning in Smart Cities and its use cases 9.Federated Deep Learning for Cyber-Physical Systems in Real-World Scenarios 10.? Use-Cases and Scenarios for Federated Learning Adoption in IoT.

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This book explores the applications and advancements of Federated Learning across diverse sectors, focusing on its integration with cutting-edge technologies like IoT, AI, Blockchain, and Digital Twins.?

This book explores the applications and advancements of federated learning across diverse sectors, focusing on its integration with cutting- edge technologies like Internet of Things (IoT), artificial intelligence (AI), blockchain, and digital twins. Real-world examples and case studies illustrate federated learnings role in healthcare, smart cities, and maritime applications while addressing critical concerns such as security. It provides insights into federated learnings transformative potential, offering practical strategies for intelligent systems and sustainable environments.

The book particularly:

• Focuses on the federated learningbased model optimization, addressing the significance of IoT and federated learning in the evolution of intelligent systems for various applications
• Describes the different optimizationlóÎ